Electronic nose devices perform odor detection through the use of an array of cross-reactive sensors in conjunction with pattern recognition methods. In contrast to the “lock-and-key” model, each sensor in the electronic nose device is widely responsive to a variety of odorants. In this architecture, each analyte produces a distinct signature from the array of broadly cross-reactive sensors. This configuration allows to considerably widen the variety of compounds to which a given matrix is sensitive, to increase the degree of component identification and, in specific cases, to perform an analysis of individual components in complex multi-component mixtures. Pattern recognition algorithms can then be applied to the entire set of signals, obtained simultaneously from all the sensors in the array, in order to acquire information on the identity, properties and concentration of the vapor exposed to the sensor array. Various algorithms and computer controlled systems for olfactometry known in the art are disclosed for example in U.S. Pat. Nos. 6,411,905, 6,606,566, 6,609,068, 6,620,109, 6,767,732, 6,820,012, and 6,839,636, among others.
Micro-organisms produce patterns of volatile organic compounds (VOCs) that are affected by the type and age of culture media. Patterns of VOCs can also be used as biomarkers of various diseases, e.g., acute asthma, uremia, cirrhosis, cystinuria, trimethylaminuria, etc. These disease biomarkers can be found in the bodily fluids of a patient, including in the serum, urea, and breath. Characteristic VOCs display different patterns at different stages of the disease.
Various devices and methods for VOC detection and analysis are disclosed, for instance, in U.S. Pat. Nos. 6,319,724, 6,411,905, 6,467,333, 6,606,566, 6,609,068, 6,620,109, 6,703,241, 6,767,732, 6,820,012, 6,839,636, 6,841,391, and in U.S. Pat. Appl. No. 2001/0041366. A transition metal oxide gas sensor is disclosed and described in U.S. Pat. No. 6,173,602.
Excluding a few individual instances, the detection levels of these devices are in the range of 1-100 parts per million (ppm). In order to detect VOCs with higher sensitivity, pre-concentrating the vapors to be detected prior to measurement is required. Consequently, real-time measurement of minute quantities of VOCs remains a challenge.
The use of Gas-Chromatography (GC), GC-lined Mass-Spectroscopy (GC-MS), Quartz Crystal Microbalance (QCM) as well as other comparable techniques for analysis of volatile biomarkers indicative of certain diseases, is impeded by several factors. These factors include the need for expensive equipment, the degree of expertise required to operate such instruments, the length of time required to obtain data acquisition, and other technical problems in sampling, data analysis, etc. Mostly, the GC-MS technique is limited to the ppm level of concentrations, while many disease biomarkers are present at concentration levels of less than one part per billion (ppb).
Similar to olfactory receptors, increased sensitivity as well as on/off rates of chemical sensors is typically achieved by reducing the dimensions of the sensing apparatus. Chemical sensors made of nanomaterials are more sensitive, more controlled, and more suitable to differentiate between subtle differences in mixtures of volatile biomarkers. Silicon nanowires (Si NWs) offer unique opportunities for signal transduction associated with selective recognition of biological or chemical species of interest.
Oxide-coated silicon nanowire field effect transistors (Si NW FETs) have been modified with amino siloxane functional groups to impart high sensitivity towards pH (Patolsky and Lieber, Mater. Today, 2005, 8: 20-28). The Si NW field effect transistors were further modified with a variety of biological receptors to selectively detect biological species in solution. Oxide-coating of a Si NW is believed to induce trap states at the Si/Si-oxide interface thus acting as a dielectric layer. This in turn lowers and consequently limits the effect of gate voltage on the transconductance of Si NW field effect transistors. This limitation affects the response of sensors based on oxide-coated Si NW field effect transistors to their environment. In a typical SiO2-coated Si NW field effect transistor, the transconductance responds weakly to the applied gate voltage, Vg, where conductivity changes by two orders of magnitude between Vg=−5V and Vg=+5 V, with no significant on/off state transition within this gate-bias region. This behavior is compatible with the characteristics of oxidized Si wherein both the Si/SiO2 interface and the SiO2 surface defects trap and scatter carriers, and as a result, decrease the effect of Vg (Lupke, Surf Sci. Rep., 1999, 35:75-161). On the contrary, devices that are based on non-oxidized Si NWs as well as those based on macroscopic planar Si (111) surfaces, exhibit low interface state density. Yet, non-oxidized Si NWs as well as Si surfaces that are terminated with hydrogen tend to undergo oxidation upon exposure to ambient conditions, resulting in the formation of defects in the sensors.
It has been reported by the inventor of the present invention, that Si NWs modified by covalent binding to a methyl functional group, show atmospheric stability, high conductance values, and less surface defects. These methyl functionalized Si NWs were shown to form air-stable Si NW field effect transistors having on-off ratios in excess of 105 over a relatively small (±2 V) gate voltage swing (Haick et al., J. Am. Chem. Soc., 2006, 128: 8990-8991). However, exposure of these methyl-functionalized devices to analytes barely provides sensing responses, most probably due to the low ability of the methyl groups to adsorb vapor/liquid analytes. Further modifications of the methyl functional groups for sensing applications at minute concentration down to the ppb levels, are not feasible.
Hence, there is an unmet need for a highly sensitive reliable device to analyze mixtures of volatile organic compounds. Furthermore, there is an unmet need for an inexpensive, efficient, convenient, reliable, and portable device to analyze mixtures of volatile biomarkers.